In this paper we address the problem of robustly estimating the position of randomly deployed nodes of a Wireless Sensor Network (WSN), in the presence of security threats. We prop...
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Modeling and predicting of mental workload are among the most important issues in studying human performance in complex systems. Ample research has shown that the amplitude of the ...
We propose a novel approach to reducing energy consumption in sensor networks using a distributed adaptive signal processing framework and efficient algorithm 1 . While the topic o...
— Measuring network flow sizes is important for tasks like accounting/billing, network forensics and security. Per-flow accounting is considered hard because it requires that m...